A Subgrid Parameterization for Wind Turbines inWeather Prediction Models with an Application to Wind Resource Limits

2016 ◽  
pp. 123-140 ◽  
Keyword(s):  
Wind Turbines ◽  
Prediction Models ◽  
Wind Resource

scholarly journals A Subgrid Parameterization for Wind Turbines in Weather Prediction Models with an Application to Wind Resource Limits

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
B. H. Fiedler ◽  
A. S. Adams
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Prediction Models ◽  
Weather Prediction ◽  
Electrical Power ◽  
Power Production ◽  
Wind Resource

A subgrid parameterization is offered for representing wind turbines in weather prediction models. The parameterization models the drag and mixing the turbines cause in the atmosphere, as well as the electrical power production the wind causes in the wind turbines. The documentation of the parameterization is complete; it does not require knowledge of proprietary data of wind turbine characteristics. The parameterization is applied to a study of wind resource limits in a hypothetical giant wind farm. The simulated production density was found not to exceed1 W m−2, peaking at a deployed capacity density of5 W m−2and decreasing slightly as capacity density increased to20 W m−2.

scholarly journals Verification of the Reliability of Offshore Wind Resource Prediction Using an Atmosphere–Ocean Coupled Model

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 254
Author(s):  
Minhyeop Kang ◽  
Kyungnam Ko ◽  
Minyeong Kim
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Prediction Models ◽  
Wrf Model ◽  
Coupled Model ◽  
Sea Surface ◽  
Offshore Wind ◽  
Wind Effect ◽  
Observation Data ◽  
Wind Resource

An atmosphere–ocean coupled model is proposed as an optimal numerical prediction method for the offshore wind resource. Meteorological prediction models are mainly used for wind speed prediction, with active studies using atmospheric models. Seawater mixing occurring at sea due to solar radiation and wind intensity can significantly change the sea surface temperature (SST), an important variable for predicting wind resources and energy production, considering its wind effect, within a short time. This study used the weather research forecasting and ocean mixed layer (WRF-OML) model, an atmosphere–ocean coupled model, to reflect time-dependent SST and sea surface fluxes. Results are compared with those of the WRF model, another atmospheric model, and verified through comparison with observation data of a meteorological mast (met-mast) at sea. At a height of 94 m, the wind speed predicted had a bias and root mean square error of 1.09 m/s and 2.88 m/s for the WRF model, and −0.07 m/s and 2.45 m/s for the WRF-OML model, respectively. Thus, the WRF-OML model has a higher reliability. In comparing to the met-mast observation data, the annual energy production (AEP) estimation based on the predicted wind speed showed an overestimation of 15.3% and underestimation of 5.9% from the WRF and WRF-OML models, respectively.

scholarly journals Wind resource characteristics and energy yield for micro wind turbines integrated on noise barriers – An experimental study

2020 ◽  
Vol 203 ◽  
pp. 104206 ◽  
Author(s):  
Nikolaos Chrysochoidis-Antsos ◽  
Andrea Vilarasau Amoros ◽  
Gerard J.W. van Bussel ◽  
Sander M. Mertens ◽  
Ad J.M. van Wijk
Keyword(s):  
Experimental Study ◽  
Wind Turbines ◽  
Energy Yield ◽  
Noise Barriers ◽  
Resource Characteristics ◽  
Wind Resource

Experimental Comparison of Three Floating Wind Turbine Concepts

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Andrew J. Goupee ◽  
Bonjun J. Koo ◽  
Richard W. Kimball ◽  
Kostas F. Lambrakos ◽  
Habib J. Dagher
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Operating Conditions ◽  
Scale Model ◽  
Experimental Comparison ◽  
System Response ◽  
Advantages And Disadvantages ◽  
Floating Wind Turbine ◽  
Wind Resource

Beyond many of Earth's coasts exists a vast deepwater wind resource that can be tapped to provide substantial amounts of clean, renewable energy. However, much of this resource resides in waters deeper than 60 m where current fixed bottom wind turbine technology is no longer economically viable. As a result, many are looking to floating wind turbines as a means of harnessing this deepwater offshore wind resource. The preferred floating platform technology for this application, however, is currently up for debate. To begin the process of assessing the unique behavior of various platform concepts for floating wind turbines, 1/50th scale model tests in a wind/wave basin were performed at the Maritime Research Institute Netherlands (MARIN) of three floating wind turbine concepts. The Froude scaled tests simulated the response of the 126 m rotor diameter National Renewable Energy Lab (NREL) 5 MW, horizontal axis Reference Wind Turbine attached via a flexible tower in turn to three distinct platforms, these being a tension leg-platform, a spar-buoy, and a semisubmersible. A large number of tests were performed ranging from simple free-decay tests to complex operating conditions with irregular sea states and dynamic winds. The high-quality wind environments, unique to these tests, were realized in the offshore basin via a novel wind machine, which exhibited low swirl and turbulence intensity in the flow field. Recorded data from the floating wind turbine models include rotor torque and position, tower top and base forces and moments, mooring line tensions, six-axis platform motions, and accelerations at key locations on the nacelle, tower, and platform. A comprehensive overview of the test program, including basic system identification results, is covered in previously published works. In this paper, the results of a comprehensive data analysis are presented, which illuminate the unique coupled system behavior of the three floating wind turbines subjected to combined wind and wave environments. The relative performance of each of the three systems is discussed with an emphasis placed on global motions, flexible tower dynamics, and mooring system response. The results demonstrate the unique advantages and disadvantages of each floating wind turbine platform.

Assessing Wind Resource Potential in the Built Environment

2011 ◽  
Author(s):  
Susan W. Stewart ◽  
Sue Ellen Haupt ◽  
Julia A. Cole
Keyword(s):  
Built Environment ◽  
Power Density ◽  
Wind Turbines ◽  
Field Measurements ◽  
Detached Eddy Simulation ◽  
Existing Structures ◽  
Eddy Simulation ◽  
Power Maps ◽  
Wind Resource ◽  
Over The Top

This study addresses the issue of siting wind turbines on existing structures in the built environment for optimal performance. Annually averaged wind power maps were produced over the surface of two different building types using a Detached Eddy Simulation (DES) model in order to assess the feasibility of building integrated wind under various wind resource conditions. The modeling approach was first applied to a cubical geometry for which validation of the CFD results was possible with existing field measurements. A pitched roof building was also modeled to study the power density over top of typical residential shaped structures. The average annual power density for twenty-seven locations over the top of the modeled structures was analyzed under varying wind direction distributions (wind roses). The overall results of this study have the potential to inform the wind energy and built environment communities on best practices for siting wind turbines on or near buildings.

scholarly journals Small wind turbines study and integration in a peri-urban microgrid

2021 ◽  
Author(s):  
Paula Peña-Carro ◽  
Óscar Izquierdo-Monge ◽  
Luis Hernández-Callejo ◽  
Gonzalo Martín-Jiménez
Keyword(s):  
Wind Turbines ◽  
Urban Environments ◽  
Wind Speeds ◽  
Small Wind Turbines ◽  
Micro Power ◽  
The Cost ◽  
Wind Resource ◽  
Wind Resources ◽  
Selection Of ◽  
Instantaneous Control

The use of wind resources has always gone hand in hand with high wind speeds in open fields. This paper develops the decisions to be taken for the selection, installation, and connection of small wind turbines in peri-urban environments, where wind speeds are medium or low. The guidelines are detailed throughout the document, starting with the study of the wind resource, the selection of the turbine, installation, and real-time monitoring of production for integration into a micro power grid. The installation of small wind systems in places as close as possible to the point of demand makes it possible to achieve a reduction in the cost of the electricity bill. This is thanks to the instantaneous control of generation and demand at a particular level through the installation of software, in this case, Home Assistant. The novelty of this paper is the use of this software Home Assistant to integrate of a small wind turbine in a microgrid and its control system.

scholarly journals Wind Turbine Anomaly Identification Based on Improved Deep Belief Network with SCADA Data

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xiafei Long ◽  
Shengqing Li ◽  
Xiwen Wu ◽  
Zhao Jin
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Domain Knowledge ◽  
Wind Farm ◽  
Prediction Models ◽  
Moving Average ◽  
Pearson Correlation ◽  
Whale Optimization

This article presents a novel fault diagnosis algorithm based on the whale optimization algorithm (WOA)-deep belief networks (DBN) for wind turbines (WTs) using the data collected from the supervisory control and data acquisition (SCADA) system. Through the domain knowledge and Pearson correlation, the input parameters of the prediction models are selected. Three different types of prediction models, namely, the wind turbine, the wind power gearbox, and the wind power generator, are used to predict the health condition of the WT equipment. In this article, the prediction accuracy of the models built with these SCADA sample data is discussed. In order to implement fault monitoring and abnormal state determination of the wind power equipment, the exponential weighted moving average (EWMA) threshold is used to monitor the trend of reconstruction errors. The proposed method is used for 2 MW wind turbines with doubly fed induction generators in a real-world wind farm, and experimental results show that the proposed method is effective in the fault diagnosis of wind turbines.

Sign in / Sign up

Export Citation Format

Share Document